United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS), Research and Development Division (RDD), Geospatial Information Branch (GIB), Spatial Analysis Research Section (SARS)
Title: USDA NASS Disaster Analysis 2020 Event - Hurricane Laura
Edition: USDA NASS Disaster Analysis 2020 Event - Hurricane Laura
Geospatial_Data_Presentation_Form: raster digital data
USDA, NASS Marketing and Information Services Office, Washington, D.C.
Publisher: USDA, NASS
The USDA NASS monitors the impact of natural disasters on US agriculture in near real-time using remotely sensed data and geospatial techniques. The first test case is detailed in the following papers <https://www.nass.usda.gov/Research_and_Science/Disaster-Analysis/2018/Hurricane-Michael/Flood_Monitoring_Methodology_Paper.pdf> and <https://www.nass.usda.gov/Research_and_Science/Cropland/docs/Boryan_IGARSS2018%20_Flood.pdf>.
This dataset evaluates the impact of Hurricane Laura on agricultural land cover. The inundation raster layer was created to estimate the extent of cropland and pasture/hay inundated by flooding that occurred in late August 2020. The official website <https://www.nass.usda.gov/Research_and_Science/Disaster-Analysis/> provides disaster assessments in geospatial data format, reports, and metadata as available. The study area consists of portions of Louisiana, Arkansas, and Mississippi, United States of America. Data represent cropland, inundated cropland,pasture/hay, inundated pasture/hay, water bodies, and other land. These data are not official NASS estimates.
Agricultural disaster monitoring is important for food security and economic stability. Using remotely sensed data and geospatial techniques provides an additional tool for the USDA NASS to use in evaluating a disaster's impact on US agriculture.
LIST OF INPUTS
Sentinel-1A Data: interferometric wide (IW) swath (250 kilometer),
Level-1 Ground Range Detected (GRD), 5x20 meter spatial resolution, and
dual polarization (VV, VH)
Imagery Download: Alaskan Satellite Facility
Pre-Flood Sentinel 1A Imagery: August 15, 16, 20, 22
Post-Flood Sentinel 1A Imagery: September 1, 2, 3, 4
Land Cover Inputs
NASS 2019 Cultivated Layer (planted acres)
Obtained From: https://www.nass.usda.gov/Research_and_Science/Cropland/Release/index.php
NASS 2019 Cropland Data Layer (planted acres)
Obtained From: CropScape: https://nassgeodata.gmu.edu/CropScape/
Currentness_Reference: September 2020
Maintenance_and_Update_Frequency: None planned
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: farming, 001
Theme_Keyword: environment, 007
Theme_Keyword: imageryBaseMapsEarthCover, 010
Theme_Keyword_Thesaurus: Global Change Master Directory (GCMD) Science Keywords
Earth Science > Biosphere > Terrestrial Ecosystems > Agricultural Lands
Theme_Keyword: crop cover
Theme_Keyword: land cover
Theme_Keyword: crop estimates
Theme_Keyword: UK-DMC 2
Theme_Keyword: ISRO ResourceSat-2 LISS-3
Theme_Keyword: ESA SENTINEL-2
Place_Keyword_Thesaurus: Global Change Master Directory (GCMD) Location Keywords
Place_Keyword: Continent > North America > United States of America > Arkansas
Continent > North America > United States of America > Louisiana
Continent > North America > United States of America > Mississippi
The USDA NASS Disaster Analysis data are provided to the public as is and are considered public domain and free to redistribute. The USDA, NASS does not warrant any conclusions drawn from these data. These data are not official NASS estimates.
Data_Set_Credit: USDA, National Agricultural Statistics Service
Contact_Organization: USDA, NASS, Spatial Analysis Research Section
Contact_Person: USDA, NASS, Spatial Analysis Research Section staff
Address_Type: mailing and physical address
Address: 1400 Independence Avenue, SW, Room 5029 South Building
State_or_Province: District of Columbia
Microsoft Windows 7 Enterprise; ERDAS Imagine Version 2018 <https://www.hexagongeospatial.com/>; ESRI ArcGIS Version 10.7.0.10450 <https://www.esri.com/>. ERDAS Imagine is used in the analysis and post-processing of all raster-based data. ESRI ArcGIS is used to prepare all vector-based data and to create graphics. The Hurricane Laura inundation data layer was created within Google Earth Engine (GEE). The use of GEE was a proof of concept for a modified processing methodology.